SIF 3rd Cohort Fellows - Ru Li, Vrije Universiteit Brussel

Curriculum Vitae
  • Education
2012: PhD in Chemistry and Physics of Polymers, University of Chinese Academy of Sciences (China)

2007: BA in Applied Chemistry, Henan University (China)


  • Experience

March 2022-October 2023: Postdoc, Delft University of Technology, Research on the component level ageing test for further modelling in AI powered digital twin in lighting industry.

August 2016-February 2022: Senior engineer, Changzhou Xingyu Automotive Lighting System Co. Ltd. Research on the new materials and technologies for the thermal dissipation and defogging of automotive lighting

July 2012-July 2016: Senior engineer/Quality Supervisor, LiteOn Optoelectronics(Changzhou), Research on the reliability, failure analysis, process technology and supplier quality management of LED devices and lighting products.

  • Publications/Research achievements
Research Project:

Design, Optimization and Risk Assessment of Lighting Future Automated Vehicles for Vulnerable Road Users

Safety, comfort and aesthetics require lighting functions to evolve and become smarter and smarter for vehicles. External human-machine interaction (eHMI) is a new feature for automotive lighting to improve vehicle communication with other road users, especially for the vulnerable road users in the context of increasingly automated vehicles above L3. However, such advanced capabilities are still being debated to be used on the road in the context of whether or not such technologies can provide a clear and understandable message to road users in a specific scenario or lead to ambiguity and anticipation.

The research will integrate the virtual and physical worlds to promote innovations in the competitive fields of the eHMI lighting industry. It will utilize simulated scenarios through a high degree of immersion through virtual reality technology which offers the possibility of setting up pedestrian simulators in which future traffic concepts can be examined with highly automated vehicles. Also, the research will examine the various physiological, cognitive, and behavioral reactions in humans when they interact with designed and optimized lighting and signaling devices in different highly automated driving scenarios. Finally, a risk assessment will be implemented to evaluate the possibility and acceptance of the designed lighting and signaling devices.